Item talk:Q46202
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orcid:
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usgs_staff_profile:
meta: url: https://www.usgs.gov/staff-profiles/angela-fuller timestamp: '2024-01-30T13:52:00.190407' status_code: 200 profile: name: Angela Fuller, PhD name_qualifier: null titles: - Research Wildlife Biologist organizations: - !!python/tuple - Cooperative Research Units - https://www.usgs.gov/programs/cooperative-research-units email: afuller@usgs.gov orcid: 0000-0002-9247-7468 intro_statements: - Unit Leader - New York Cooperative Fish and Wildlife Research Unit expertise_terms: - wildlife management - statistics and modeling - ecology professional_experience: - Unit Leader, New York Cooperative Fish and Wildlife Research Unit, 2014- - Assistant Unit Leader, New York Cooperative Fish and Wildlife Research Unit, 2009-2014 education: - Ph D University of Maine 2006 - MS University of Maine 1999 - BS University of Maine at Machias 1996 affiliations: [] honors: [] abstracts: [] personal_statement: Research InterestsThe single unifying theme of Angela's research program that transcends all projects is that they provide information that contributes to the conservation or management of wildlife species and that has an impact on the way species are managed. The first area of her research is on how spatial variation in the environment influences resource use, movements, and population ecology of mammals. This research is focused primarily on mammalian carnivores, which have many traits that make them especially susceptible to landscape change (e.g., large home ranges, relatively low population densities, and long dispersal distances). She frequently uses non-invasive sampling methods that do not require direct capture of individuals. Using these noninvasively collected samples from carnivores, she employs methods for population estimation that incorporate spatial or landscape processes to help explain the density of species across a landscape. The second major program area of her research is in applying structured decision making (SDM) and adaptive management to guide natural resource management and policy outcomes. SDM is a process for helping to make management or policy decisions in a clear and transparent way, and involves evaluating how well alternative management strategies do at achieving objectives that have been identified by the decision maker and stakeholders. This work integrates quantitative modeling to help predict outcomes of the management strategies that were developed to achieve the stated objectives. Both of her research areas involve the spatial ecology of species, investigating how spatial landscape patterns influence the distribution, density, or dynamics of animal populations.Teaching InterestsDecision Making for Natural ResourcesLandscape EcologyHabitat EcologyForest Landscape Planning